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Record W3161361220

High altitude sports and entertainment: Select case studies

2021· article· en· W3161361220 on OpenAlexaboutno aff
Bijender Singh, Sandeep Bhalla

Bibliographic record

VenueInternational Journal of Physical Education Sports and Health · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHigh Altitude and Hypoxia
Canadian institutionsnot available
Fundersnot available
KeywordsEntertainmentAltitude (triangle)Effects of high altitude on humansElevation (ballistics)RecreationAdvertisingGeographyMeteorologyEngineeringBusinessArtEcologyVisual artsBiology
DOInot available

Abstract

fetched live from OpenAlex

High altitude sports are generally most entertaining and safe for recreational tourists/athletes, but they should be aware of their individual risks. It is a well-known fact that there is less oxygen at higher elevation. When looking at the effective oxygen content of air at altitude compared to sea level, there is 15% less oxygen at 5,000 feet (elevation of Denver), 26% less oxygen at 8,000 feet (elevation of Aspen), and 41% less oxygen at 14,000 feet (elevation of the Colorado 14ers)! [ ] So high altitudes make it harder to breath. The benefits of training at such high altitudes include: Get better endurance due to increased red blood cell count; perform better at high and low altitudes; because you get to train in places which are most scenic and best for adventure sports and entertainment; etc. Select case studies, to get more details about high altitude sports and entertainment at a global level, include: Kroenke Sports & Entertainment (KSE), USA; Altitude Sports, USA; Calgary Sports and Entertainment Corporation (CSEC), Canada; and True North Sports and Entertainment Limited (TNSE), Canada.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.538
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.361
Teacher spread0.347 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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